Develop large-scale distributed data processing applications using Spark 2 in Scala and Python About This Book This book offers an easy introduction to the Spark framework published on the latest version of Apache Spark 2 Perform efficient data processing, machine learning and graph processing using various Spark components A practical guide aimed at beginners to get them up and running with Spark Who This Book Is For If you are an application developer, data scientist, or big data solutions architect who is interested in combining the data processing power of Spark from R, and consolidating data processing, stream processing, machine learning, and graph processing into one unified and highly interoperable framework with a uniform API using Scala or Python, this book is for you. What You Will Learn Get to know the fundamentals of Spark 2 and the Spark programming model using Scala and Python Know how to use Spark SQL and DataFrames using Scala and Python Get an introduction to Spark programming using R Perform Spark data processing, charting, and plotting using Python Get acquainted with Spark stream processing using Scala and Python Be introduced to machine learning using Spark MLlib Get started with graph processing using the Spark GraphX Bring together all that you've learned and develop a complete Spark application In Detail Spark is one of the most widely-used large-scale data processing engines and runs extremely fast. It is a framework that has tools that are equally useful for application developers as well as data scientists. This book starts with the fundamentals of Spark 2 and covers the core data processing framework and API, installation, and application development setup. Then the Spark programming model is introduced through real-world examples followed by Spark SQL programming with DataFrames. An introduction to SparkR is covered next. Later, we cover the charting and plotting features of Python in conjunction with Spark data processing. After that, we take a look at Spark's stream processing, machine learning, and graph processing libraries. The last chapter combines all the skills you learned from the preceding chapters to develop a real-world Spark application. By the end of this book, you will have all the knowledge you need to develop efficient large-scale applications using Apache Spark. Style and approach Learn about Spark's infrastructure with this practical tutorial. With the help of real-world use cases on the main features of Spark we offer an easy introduction to the framework.
As our society transforms into a data-driven one, the role of the Data Scientist is becoming more and more important. If you want to be on the leading edge of what is sure to become a major profession in the not-too-distant future, this book can show you how. Each chapter is filled with practical information that will help you reap the fruits of big data and become a successful Data Scientist: • Learn what big data is and how it differs from traditional data through its main characteristics: volume, variety, velocity, and veracity. • Explore the different types of Data Scientists and the skillset each one has. • Dig into what the role of the Data Scientist requires in terms of the relevant mindset, technical skills, experience, and how the Data Scientist connects with other people. • Be a Data Scientist for a day, examining the problems you may encounter and how you tackle them, what programs you use, and how you expand your knowledge and know-how. • See how you can become a Data Scientist, based on where you are starting from: a programming, machine learning, or data-related background. • Follow step-by-step through the process of landing a Data Scientist job: where you need to look, how you would present yourself to a potential employer, and what it takes to follow a freelancer path. • Read the case studies of experienced, senior-level Data Scientists, in an attempt to get a better perspective of what this role is, in practice. At the end of the book, there is a glossary of the most important terms that have been introduced, as well as three appendices – a list of useful sites, some relevant articles on the web, and a list of offline resources for further reading.
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Chiefly Devoted to Library Economy and Bibliography
Includes, beginning Sept. 15, 1954 (and on the 15th of each month, Sept.-May) a special section: School library journal, ISSN 0000-0035, (called Junior libraries, 1954-May 1961). Also issued separately.